THE FUTURE OF D A T A TECHNOLOGY
IN BANKING INDUSTRY
Jakarta, March 2019
WHAT IS DATA TECHNOLOGY ?
A technology that can generates data, transmits,
stores, analyzes, and extracts it to become a value.
IS DATA THE NEW OIL ?
• Exponential Value
• Spread Sources
• No Piping Distribution.
• Unlimited Resources
Data Generation Value Creation Value Delivery
What What What
• Capturing existing data. • Datawarehouse & big data. • Business cases
• Create new data from • Machine Learning. Who
existing system. • Artificial Intelligence. • Data business company
• Create new sources of data. Who How
Who • Big data talent. • One-on-one relationship.
• Technology for everyone. • Data scientist.
• Focus on external data. • Autonomous Agent.
• Customer collaboration. How
How • Integrate data.
• Know-It-All. • Intelligence Automation.
• Plug and play. • Be Digital.
• Real-time streaming.
Issues
• Privacy
DATA GENERATION, WHAT?
Capturing Existing Data
• We have too many sources.
• No integration.
• No single unique id.
Create New Data from Existing System
• We need time to develop.
Create New Sources of Data
• How to collaboration with 3rd party?
DATA GENERATION, WHO?
Focus on External Data
• Data originally by customer.
Technology for Everyone
• Everyone is data producer.
• Led by technology.
Customer Collaboration
• Customer customized UI by
themselves (sample).
• Customer voices (sample).
DATA GENERATION, HOW?
Know It All.
• Change everything to be code
generator.
• Know everything
Plug and Play.
• No need to train customer.
Based on the research of
Cognizant Center for the Future of Work Real-time Streaming.
(Frank, Roehrig, Pring, 2018) • Need to real time analysis.
VALUE CREATION, WHAT?
Datawarehouse & Big Data
• 5V : Volume, Velocity, Variety, Veracity, Value.
• Hardware & software now available to process
huge amount of data.
Machine Learning
• Predictive & prescriptive analytics.
• Supervised and unsupervised learning.
• Efficient algorithms.
Artificial Intelligence
• General AI vs Narrow AI.
VALUE CREATION, WHO?
Big Data Talent.
• Data ingestion & synchronization.
• To process several types of data.
• Big data analytics.
• To process huge amount of data.
Data Scientist.
• Very scarce resource.
Autonomous Agent
• Robotic Process Automation.
• Intelligent Automation.
Which area should be automated?
VALUE CREATION, HOW? 66% 68% 71% 75%
Integrate data.
• More exponential values.
Intelligence Automation.
• Automation is not a choice.
• IA = RPA + AI
Be Digital.
Post-trade Wealth New Product Front Office
• Not just doing digital. Processing / Management / Service
Back-office Creation
Based on the research of Cognizant Center for the Future of Work
(Frank, Roehrig, Pring, 2018)
VALUE DELIVERY, WHAT?
Business Cases
• How to choose proper business
cases?
Social Media
Ideas from : Interaction
• Attribute listing.
• Forced relationships.
• Morphological analysis.
• Reverse assumption analysis.
• New contexts.
• Mind mapping.
Empower with :
Advanced analytics /
Based on the research of Cognizant Center for the Future of Work
machine learning. (Frank, Roehrig, Pring, 2018)
VALUE DELIVERY, WHO?
Data Business Company
• How to monetize your data?
• Data as a service.
• Information as a service.
• Answers as a service.
VALUE DELIVERY, HOW?
One-on-One Relationship
• Focus on “verb” not “noun”.
• Begin on small things.
Menu • Create new experience for
Transaction
Reminder customers.
• Right value for every single
customer.
Product • Direct communication.
Promo
Recommendation
References :
• Frank, Malcolm, Roehrig, Paul, Pring, Ben, 2018, Apa yang Harus Dilakukan
Ketika Mesin Melakukan Semuanya, PT Elex Media Computindo, Jakarta
• http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html
• https://www.businessmodelsinc.com/big-data-business-models/
• https://www.forbes.com/sites/bernardmarr/2016/03/15/17-predictions-
about-the-future-of-big-data-everyone-should-read/#44affecc1a32
T H A N K • Kelly, Tom, Littman, Jonathan, 2002, The Art of Innovation, PT Gramedia
Pustaka Utama, Jakarta
• Kotler, Philip, Keller, Kevin L., 2009, Marketing Management, 13th Edition,
Y O U •
Pearson Education, Inc., New Jersey
Tapscott, Don, Williams, Anthony D., 2008, Wikinomics, PT Bhuana Ilmu
Populer, Kelompok Gramedia, Jakarta
Special Thanks to :
• https://pixabay.com for amazing pictures.
• https://www.iconfinder.com
• https://www.pexels.com for amazing pictures.
